Project Summary Understanding human aging requires us to perform experiments directly with human. This can be challenging due to ethical barriers, high cost, long human lifespan and several other factors. On the other hand, a deluge of human genomic data have emerged and some of them have outstanding potentials to be repositioned for aging research. Leveraging existing human data for aging research provides an economically efficient, time- saving solution to overcome the many obstacles associated with human experiments. We propose to go deep in analyzing a very unique and unprecedented large scale human genomic dataset for aging research. This dataset as generated from GTEx (Genotype of Tissue Expression) project represents a rare opportunity for studying human aging gene expressions and genetics at multi-tissue level. We propose to work on four specific aims: first, we will define human aging gene expression signatures in more than 40 tissue types. For many tissues, this is the first time to reveal their aging gene expression change patterns. We will also investigate disease and sex influence on these aging gene expression and find conserved aging mechanisms from model organisms to human. Second, early studies have shown that different parts of human body age at different rates, but it is unknown if the biological ages of different tissues are under higher order coordination. Our work is to investigate on this topic to confirm our previous finding on the coordinated aging among tissues. We will also test if tissue co-aging correlates with disease comorbidity. Third, we will look into the genetic regulation on age-related gene expression in various tissues. We will test if genetic variants associated with aging gene expression could also be associated with human longevity or age-related diseases. Fourth, we will select top variants and experimentally validate the causal regulation on gene expression. We believe all these questions are important for human aging research; the answers to these questions will significantly help us to better understand human aging and help translational research.